﻿The determination of the concession period length is one of the most important
decisions undertaken during the life span of a Build-Operate-Transfer project. The
concession period length directly affects both the involved government and private
investors' financial returns and risks, and offers significant economic and social benefits.
In existing methods, the concession period is usually determined by the concessionaire,
depending on their expected investment return using the payback period method or it is
predicted without comprehensive analysis of the influential factors. In view of this, a
Decision Support System for concession period length determination (CPLD) was
developed and, as demonstrated herein provides a possible way of solving the
concession period problem, especially under the impact of various influential factors.
In the proposed Decision Support System, an overall model for CPLD, and two
sub-models for predicting the key variables of CPLD were developed. Since the
length of the concession period is under impact from various factors, an in-depth
investigation of the influential factors was firstly conducted, in which the selection,
classification, and ranking of the influential factors were concerned. Thus the input
variables for the models involved in this system were generated. Then two sub-models
were developed to predict the key variables (Traffic flow and Toll fee) of concession
period length, so as to make the overall model for CPLD reliable and perform smoothly.
Additionally, a Variable Evaluation System was constructed. The input variables
involved in the model were tested in this section. Thus the degree of importance of each
variable was obtained. Finally, the overall model for CPLD was developed. The established model does not mean to achieve the highest profit for any side (either the
government or the private sector); rather it means a balance of the two extreme sides
within the same decision-making process.
Two datasets of tunnel projects in Hong Kong were constructed to verify the prediction
models. A dataset of a simulated highway project was employed for training the overall
model of CPLD. The experimental results show that the proposed method and system
can provide the decision makers with a set of alternatives, among which an optimal one
can be selected after balancing the interests of both the government and private sectors.
Thus the Decision Support System was developed. It is expected that the proposed DSS
can assist the decision-making process of concession period length determination, and
finally contribute both theoretical and practical knowledge for academics and
practitioners in the field.